西安电子科技大学学报 ›› 2016, Vol. 43 ›› Issue (2): 199-204.doi: 10.3969/j.issn.1001-2400.2016.02.034

• 研究论文 • 上一篇    

针对有向社交网络的Sybil检测方法

王永程1;孟艳红2   

  1. (1. 盲信号处理国家重点实验室,四川 成都  610041;
    2. 西安电子科技大学 通信工程学院,陕西 西安  710071)
  • 收稿日期:2015-09-03 出版日期:2016-04-20 发布日期:2016-05-27
  • 通讯作者: 王永程
  • 作者简介:王永程(1987-), 男, 博士, E-mail: 407541127@qq.com.
  • 基金资助:

    国家自然科学基金资助项目(61372076,61301171);高等学校学科创新引智计划资助项目(B08038);中央高校基本科研业务费专项资金资助项目(K5051301059 ,K5051201021)

SybilGrid: Sybil detection method based on directed social networks

WANG Yongcheng1;MENG Yanhong2   

  1. (1. National Key Lab. of Science and Technology on Blind Signal Processing, Chengdu  610041, China;
    2. School of Telecommunication Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2015-09-03 Online:2016-04-20 Published:2016-05-27
  • Contact: WANG Yongcheng

摘要:

提出了一种针对有向社交网络的Sybil检测方法——SybilGrid法.该方法采用针对有向社交网络拓扑的随机游走策略来检测Sybil节点.通过采集新浪微博上的真实社交网络拓扑数据,对算法的性能进行了评估,证明了算法的有效性.与现有的SybilDefender方法进行了对比分析,对于同样数量的攻击边,SybilDefender法的虚警率为SybilGrid法的1.6倍左右;同时,为了达到相同的虚警率,SybilGrid法所需要的游走路径长度更短,即SybilGrid法的检测效率更高.

关键词: Sybil攻击, 社交网络, 随机游走

Abstract:

A Sybil detection method based on the random walk strategy is proposed to detect the Sybil nodes in the directed social network. The performance of the algorithm is evaluated by collecting the real social network topological data on Sina Weibo, and the effectiveness of the algorithm is proved. In addition, compared with the existing SybilDefender method, it is found that the false alarm rate of SybilDefender is about 1.6 times as great as SybilGrid. Meanwhile, to achive the same false alarm probability, the random walk length required by SybilGrid is much shorter, meaning that the detection efficiency of SybilGrid is higher.

Key words: Sybil attack, social networks, random walk

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